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---
license: llama2
datasets:
- bertin-project/alpaca-spanish
language:
- es
library_name: transformers
pipeline_tag: text-generation
---
## Llama 2-13b-alpaca-spanish LoRA
This is a LoRA for Llama 2 13B trained on a translated [alpaca dataset](https://huggingface.co/datasets/bertin-project/alpaca-spanish) on an attempt to improve spanish performance of the Llama-2 foundation model with a conversational focus.
Base model used was [The Bloke's Llama-2-13B-fp16](https://huggingface.co/TheBloke/Llama-2-13B-fp16) trained in 4bit precision with an added padding token.
## Important INFO
The original Llama 2 model does not have a padding token, this came to be restrictive when training. To address this, I added a padding token to the tokenizer associated with the model.
```python
from transformers import LlamaTokenizer, LlamaForCausalLM
model_name = 'TheBloke/Llama-2-13B-fp16'
model = LlamaForCausalLM.from_pretrained(model_name).half()
tokenizer = LlamaTokenizer.from_pretrained(model_name)
# Add padding token
tokenizer.add_tokens(['<PAD>'])
tokenizer.pad_token = '<PAD>'
# Resizing the model
model.resize_token_embeddings(len(tokenizer))
padded_model_name = 'Llama-2-13B-fp16-padded'
# Save
tokenizer.save_pretrained(padded_model_name)
model.save_pretrained(padded_model_name)
```
| Training parameteres | |
| ----------- | ----------- |
| LoRA scale | 2 |
| Epochs | 0.75 |
| Learning Rate| 2e-5 |
| Warmup Steps| 100 |
| Loss | 1.07 |
|